Titlebook: Scalable Uncertainty Management; Third International Lluís Godo,Andrea Pugliese Conference proceedings 2009 Springer-Verlag Berlin Heidelb

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A Model Based on Possibilistic Certainty Levels for Incomplete Databases,e about the more or less certain value (or disjunction of values) that a given attribute in a given tuple can take. This is represented in the setting of possibility theory. A relational database model suited to this context is introduced, and selection, join and union operators of relational algebr

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A Proposal for Making Argumentation Computationally Capable of Handling Large Repositories of Uncertational systems that can perform complicated inferences, obtain the appropriate conclusions, and explain the results are increasingly being required to act upon large databases. Argumentation systems could be used in the construction of interactive systems that are able to reason with large databas

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Making Sense of a Sequence of Events: A Psychologically Supported AI Implementation,ve the normal course of thing should be. An agent.s beliefs may be consonant or dissonant with what is reported. For making sense people usually ascribe different types of relations between events. A prototypical example is the ascription of causality between events. The paper proposes a systematic

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On Improving the Scalability of Checking Satisfiability in Probabilistic Description Logics,currently intractable as the existing algorithm generates exponentially large linear optimization systems. To cope with this, we employ advanced optimization techniques that do not require the systems to be fully generated before starting to solve them. One such technique, namely, column generation,

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Fast and Accurate Prediction of the Destination of Moving Objects,or . where the agent (Predictor) predicting a destination may not know anything about the route planning mechanism used by another agent (Target) nor does the agent have historical information about the target’s past movements nor do the observations about the agent have to be complete (there may be

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Probabilistic Planning with Imperfect Sensing Actions Using Hybrid Probabilistic Logic Programs, probabilistic contingent planning (probabilistic planning with imperfect sensing actions), by relating probabilistic contingent planning to normal hybrid probabilistic logic programs with probabilistic answer set semantics [24]. We show that any probabilistic contingent planning problem can be enco